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      Transactions on Computational Systems Biology VII 

      Graph Theory for Rule-Based Modeling of Biochemical Networks

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          Development of human protein reference database as an initial platform for approaching systems biology in humans.

          Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.
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            An Algorithm for Subgraph Isomorphism

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              BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains.

              BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.
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                Author and book information

                Book Chapter
                2006
                : 89-106
                10.1007/11905455_5
                55520ab9-84f3-4042-86ca-b1cd6f2aa4e7
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